The continuous expansion of the Internet, the expansion and sophistication of enterprise computing networks and systems, the proliferation of content, like movies, stored and accessible over the Internet, and numerous other factors continues to drive the need for large sophisticated data storage systems. Consequently, as the demand for data storage continues to increase, larger and more sophisticated storage systems are being designed and deployed. Many large scale data storage systems utilize storage appliances that include arrays of storage media. These storage appliances are capable of storing incredible amounts of data. For example, at this time, Oracle's SUN ZFS Storage 7420 appliance can store over 2 petabytes of data (over 2 quadrillion bytes of data). Moreover, multiple storage appliances may be networked together to form a cluster, which allows for an increase in the volume of stored data. Additionally, storage appliances arranged in a cluster may be configured to mirror data so that if one of the storage appliances becomes inoperable, the data is available at another storage location.
As the number of components, the number of users, and the volume of data increases, so does the size and complexity of the storage system. Occasionally, a client utilizing a storage system having storage appliances encounters a performance issue resulting in the appearance of: the storage appliance running slowly; an outage; or other performance degradations. Conventional diagnostic approaches are often inconsistent in addressing and resolving such performance issues. For example, many conventional diagnostic approaches begin by analyzing the storage appliance with the assumption that a fault (i.e., a failure of all or part of the storage system) exists, and as a result, often mis-identify the problem or waste time or resources. Further, conventional diagnostic approaches fail to analyze how the entire storage system is interacting in diagnosing and remedying performance issues, leaving unaddressed issues relating to the client data load applied to the storage appliance and relating to how the storage appliance and/or the client network are configured.
It is with these observations in mind, among others, that various aspects of the present disclosure were conceived and developed.